Improved criteria on delay-dependent stability for discrete-time neural networks with interval time-varying delays
type: Item
instance of: scholarly article
title: Improved criteria on delay-dependent stability for discrete-time neural networks with interval time-varying delays
zbMATH Open document ID: 1255.93101
DOI: 10.1155/2012/285931
author: Yanyan Li
published in: Abstract and Applied Analysis
publication date: 2013-02-04T00:00:00Z
review text: Summary: The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov's method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.
Mathematics Subject Classification ID: 93D05
Mathematics Subject Classification ID: 93C55
Mathematics Subject Classification ID: 92B20
Mathematics Subject Classification ID: 93D30
zbMATH DE Number: 6134052
zbMATH Keywords: delay-dependent stability analysis
zbMATH Keywords: discrete-time neural networks with interval time-varying delays
zbMATH Keywords: Lyapunov method
zbMATH Keywords: linear matrix inequalities
zbMATH Keywords: (LMIs)
zbMATH Keywords: Lyapunov-Krasovskii functional
zbMATH Keywords: reciprocally convex approach
Wikidata QID: Q57590738
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/285931
OpenAlex ID: W2170988175
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description: scientific article; zbMATH DE number 6134052